Managing queue distribution between critical datacenter and flexible datacenter

ABSTRACT

Systems include one or more critical datacenter connected to behind-the-meter flexible datacenters. The critical datacenter is powered by grid power and not necessarily collocated with the flexible datacenters, which are powered “behind the meter.” When a computational operation to be performed at the critical datacenter is identified and determined that it can be performed more efficiently or advantageously at a flexible datacenter, the computational operation is instead obtained by the flexible datacenters for performance The critical datacenter and flexible datacenters preferably share a dedicated communication pathway to enable high-bandwidth, low-latency, secure data transmissions. A queue system may be used to organize computational operations waiting for distribution to either the critical datacenter or the flexible datacenter.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 16/573,577, filed Sep. 17, 2019, which is a continuation ofU.S. patent application Ser. No. 16/525,142, filed Jul. 29, 2019 (nowU.S. Pat. No. 11,283,261), which is a continuation of U.S. patentapplication Ser. No. 16/175,335, filed Oct. 30, 2018 (now U.S. Pat. No.10,367,353). The disclosures set forth in the referenced applicationsare incorporated herein by reference in their entireties.

FIELD OF THE INVENTION

This specification relates to a system for controlling the use of“behind-the-meter” power.

BACKGROUND OF THE INVENTION

The price for power distributed through regional and national electricpower grids is composed of Generation, Administration, and Transmission& Distribution (“T&D”) costs. T&D costs are a significant portion of theoverall price paid by consumers for electricity. T&D costs includecapital costs (land, equipment, substations, wire, etc.), electricaltransmission losses, and operation and maintenance costs. Electricalpower is typically generated at local stations (e.g., coal, natural gas,nuclear, and renewable sources) in the Medium Voltage class of 2.4 kVACto 69 kVAC before being converted in an AC-AC step up transformer toHigh Voltage at 115 kVAC or above. T&D costs are accrued at the pointthe generated power leaves the local station and is converted to HighVoltage electricity for transmission onto the grid.

Local station operators are paid a variable market price for the amountof power leaving the local station and entering the grid. However, gridstability requires that a balance exist between the amount of powerentering the grid and the amount of power used from the grid. Gridstability and congestion is the responsibility of the grid operator andgrid operators take steps, including curtailment, to reduce power supplyfrom local stations when necessary. Frequently, the market price paidfor generated power will be decreased in order to disincentivize localstations from generating power. In some cases, the market price will gonegative, resulting in a cost to local station operators who continue tosupply power onto a grid. Grid operators may sometimes explicitly directa local station operator to reduce or stop the amount of power the localstation is supplying to the grid.

Power market fluctuations, power system conditions such as power factorfluctuation or local station startup and testing, and operationaldirectives resulting in reduced or discontinued generation all can havedisparate effects on renewal energy generators and can occur multipletimes in a day and last for indeterminate periods of time. Curtailment,in particular, is particularly problematic.

According to the National Renewable Energy Laboratory's Technical ReportTP-6A20-60983 (March 2014):

-   -   [C]urtailment [is] a reduction in the output of a generator from        what it could otherwise produce given available resources (e.g.,        wind or sunlight), typically on an involuntary basis.        Curtailments can result when operators or utilities command wind        and solar generators to reduce output to minimize transmission        congestion or otherwise manage the system or achieve the optimal        mix of resources. Curtailment of wind and solar resources        typically occurs because of transmission congestion or lack of        transmission access, but it can also occur for reasons such as        excess generation during low load periods that could cause        baseload generators to reach minimum generation thresholds,        because of voltage or interconnection issues, or to maintain        frequency requirements, particularly for small, isolated grids.        Curtailment is one among many tools to maintain system energy        balance, which can also include grid capacity, hydropower and        thermal generation, demand response, storage, and institutional        changes. Deciding which method to use is primarily a matter of        economics and operational practice.    -   “Curtailment” today does not necessarily mean what it did in the        early 2000s. Two sea changes in the electric sector have shaped        curtailment practices since that time: the utility-scale        deployment of wind power, which has no fuel cost, and the        evolution of wholesale power markets. These simultaneous changes        have led to new operational challenges but have also expanded        the array of market-based tools for addressing them.    -   Practices vary significantly by region and market design. In        places with centrally-organized wholesale power markets and        experience with wind power, manual wind energy curtailment        processes are increasingly being replaced by transparent        offer-based market mechanisms that base dispatch on economics.        Market protocols that dispatch generation based on economics can        also result in renewable energy plants generating less than what        they could potentially produce with available wind or sunlight.        This is often referred to by grid operators by other terms, such        as “downward dispatch.” In places served primarily by vertically        integrated utilities, power purchase agreements (PPAs) between        the utility and the wind developer increasingly contain        financial provisions for curtailment contingencies.    -   Some reductions in output are determined by how a wind operator        values dispatch versus non-dispatch. Other curtailments of wind        are determined by the grid operator in response to potential        reliability events. Still other curtailments result from        overdevelopment of wind power in transmission-constrained areas.    -   Dispatch below maximum output (curtailment) can be more of an        issue for wind and solar generators than it is for fossil        generation units because of differences in their cost        structures. The economics of wind and solar generation depend on        the ability to generate electricity whenever there is sufficient        sunlight or wind to power their facilities.    -   Because wind and solar generators have substantial capital costs        but no fuel costs (i.e., minimal variable costs), maximizing        output improves their ability to recover capital costs. In        contrast, fossil generators have higher variable costs, such as        fuel costs. Avoiding these costs can, depending on the economics        of a specific generator, to some degree reduce the financial        impact of curtailment, especially if the generator's capital        costs are included in a utility's rate base.

Curtailment may result in available energy being wasted (which may notbe true to the same extent for fossil generation units which can simplyreduce the amount of fuel that is being used). With wind generation, inparticular, it may also take some time for a wind farm to become fullyoperational following curtailment. As such, until the time that the windfarm is fully operational, the wind farm may not be operating withoptimum efficiency and/or may not be able to provide power to the grid.

BRIEF SUMMARY OF THE INVENTION

In an example, a system is described. The system includes a flexibledatacenter comprising: a behind-the-meter power input system, a firstpower distribution system, a datacenter control system, and a firstplurality of computing systems powered by the behind-the-meter powerinput system via the first power distribution system. The flexibledatacenter control system is configured to modulate power delivery tothe plurality of computing systems based on one or more monitored powersystem conditions or an operational directive. The system furtherincludes a critical datacenter comprising: a power input system, asecond power distribution system, a critical datacenter control system,and a second plurality of computing systems powered by the power inputsystem via the second power distribution system. The system furtherincludes a queue system configured to organize a plurality ofcomputational operations and a first communication link connecting theflexible datacenter, the critical datacenter, and the queue system. Thesystem also includes a routing control system configured to (i)identify, using the queue system, a computational operation to beperformed, (ii) determine whether to route the computational operationto the flexible datacenter, and (iii) based on a determination to routethe computational operation to the flexible datacenter, cause thecomputational operation to be sent to the flexible datacenter via thefirst communication link.

In another example, a system is described. The system includes aplurality of flexible datacenters, each flexible datacenter comprising:a behind-the-meter power input system, a first power distributionsystem, a datacenter control system, and a first plurality of computingsystems powered by the behind-the-meter power input system. The flexibledatacenter control system is configured to modulate power delivery tothe plurality of computing systems based on one or more monitored powersystem conditions or an operational directive. The system furtherincludes a critical datacenter comprising: a power input system, asecond power distribution system, a critical datacenter control system,and a second plurality of computing systems powered by the power inputsystem via the second power distribution system. The system alsoincludes a queue system configured to organize a plurality ofcomputational operations and a first communication link connecting theplurality of flexible datacenter, the critical datacenter, and the queuesystem. The system further includes a routing control system configuredto (i) identify, using the queue system, a computational operation to beperformed, (ii) determine whether to route the computational operationto a flexible datacenter in the plurality of flexible datacenters, (iii)based on a determination to route the computational operation to aflexible datacenter in the plurality of flexible datacenters, determinea specific flexible datacenter in the plurality of flexible datacentersto route the computational operation to, and (iv) cause thecomputational operation to be sent to the specific flexible datacentervia the first communication link.

Other aspects of the present invention will be apparent from thefollowing description and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a computing system in accordance with one or moreembodiments of the present invention.

FIG. 2 shows a flexible datacenter in accordance with one or moreembodiments of the present invention.

FIG. 3 shows a three-phase power distribution of a flexible datacenterin accordance with one or more embodiments of the present invention.

FIG. 4 shows a control distribution scheme of a flexible datacenter inaccordance with one or more embodiments of the present invention.

FIG. 5 shows a control distribution scheme of a fleet of flexibledatacenters in accordance with one or more embodiments of the presentinvention.

FIG. 6 shows a flexible datacenter powered by one or more wind turbinesin accordance with one or more embodiments of the present invention.

FIG. 7 shows a flexible datacenter powered by one or more solar panelsin accordance with one or more embodiments of the present invention.

FIG. 8 shows a flexible datacenter powered by flare gas in accordancewith one or more embodiments of the present invention.

FIG. 9A shows a method of dynamic power delivery to a flexibledatacenter using behind-the-meter power in accordance with one or moreembodiments of the present invention.

FIG. 9B shows another method of dynamic power delivery to a flexibledatacenter using behind-the-meter power in accordance with one or moreembodiments of the present invention.

FIG. 10 illustrates a system for managing queue distribution among acritical datacenter and behind-the-meter flexible datacenters inaccordance with one or more embodiments of the present invention.

FIG. 11 illustrates a system for managing queue distribution among acritical datacenter and a plurality of behind-the-meter flexibledatacenters in accordance with one or more embodiments of the presentinvention.

FIG. 12 illustrates a method for managing queue distribution between acritical datacenter and a flexible datacenter in accordance with one ormore embodiments of the present invention.

FIG. 13 illustrates a method for managing queue distribution between acritical datacenter and a plurality of flexible datacenter in accordancewith one or more embodiments of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

One or more embodiments of the present invention are described in detailwith reference to the accompanying figures. For consistency, likeelements in the various figures are denoted by like reference numerals.In the following detailed description of the present invention, specificdetails are set forth in order to provide a thorough understanding ofthe present invention. In other instances, well-known features to onehaving ordinary skill in the art are not described to avoid obscuringthe description of the present invention.

The embodiments provided herein relate to providing an electrical load“behind the meter” at local stations such that generated power can bedirected to the behind-the-meter load instead of onto the grid,typically for intermittent periods of time. “Behind-the-meter” powerincludes power that is received from a power generation system (forinstance, but not limited to, a wind or solar power generation system)prior to the power undergoing step-up transformation to High Voltageclass AC power for transmission to the grid. Behind-the-meter power maytherefore include power drawn directly from an intermittent grid-scalepower generation system (e.g. a wind farm or a solar array) and not fromthe grid.

The embodiments herein provide an advantage when, for example, the powersystem conditions exhibit excess local power generation at a localstation level, excess local power generation that a grid cannot receive,local power generation that is subject to economic curtailment, localpower generation that is subject to reliability curtailment, local powergeneration that is subject to power factor correction, low local powergeneration, start up local power generation situations, transient localpower generation situations, conditions where the cost for power iseconomically viable (e.g., low cost for power), or testing local powergeneration situations where there is an economic advantage to usinglocal behind-the-meter power generation. This is not least because theexcess power can be utilized by the behind-the-meter electrical loadrather than going to waste. In addition, by providing an electrical loadbehind-the-meter rather than connected to the grid, electricaltransmission losses resulting from transmission of power through thegrid can be reduced. In addition, any degradation in the powergeneration systems which may result from curtailment may be reduced.

Preferably, controlled computing systems that consume electrical powerthrough computational operations can provide a behind-the-meterelectrical load that can be granularly ramped up and down quickly underthe supervision of control systems that monitor power system conditionsand direct the power state and/or computational activity of thecomputing systems. In one embodiment, the computing systems preferablyreceive all their power for computational operations from abehind-the-meter power source. In another embodiment, the computingsystems may additionally include a connection to grid power forsupervisory and communication systems or other ancillary needs. In yetanother embodiment, the computing systems can be configured to switchbetween behind-the-meter power and grid power under the direction of acontrol system.

Among other benefits, a computing system load with controlled granularramping allows a local station to avoid negative power market pricingand to respond quickly to grid directives. Local stations may include astation capable of controlling power direction and supply and may bereferred to as substations or station controls. For instance, a localstation may control access to power from the power grid.

Various computing systems can provide granular behind-the-meter ramping.Preferably the computing systems perform computational tasks that areimmune to, or not substantially hindered by, frequent interruptions orslow-downs in processing as the computing systems ramp up and down. Inone embodiment, control systems can activate or de-activate one or morecomputing systems in an array of similar or identical computing systemssited behind the meter. For example, one or more blockchain miners, orgroups of blockchain miners, in an array may be turned on or off. Inanother embodiment, control systems can direct time-insensitivecomputational tasks to computational hardware, such as CPUs and GPUs,sited behind the meter, while other hardware is sited in front of themeter and possibly remote from the behind-the-meter hardware. Anyparallel computing processes, such as Monte Carlo simulations, batchprocessing of financial transactions, graphics rendering, and oil andgas field simulation models are all good candidates for suchinterruptible computational operations.

A typical datacenter provides computational resources to supportcomputational operations. Particularly, one or more enterprises mayassign computational operations to the typical datacenter withexpectations that the typical datacenter reliably provides resources tosupport the computational operations, such as processing abilities,networking, and/or storage. The computational operations assigned to atypical datacenter may vary in their requirements. Some computationaloperations may require low-latency processing, or are extremely timesensitive, or require a high degree of support and reliability from thedatacenter. Other computational operations are not time sensitive andcan be batch processed over time, or can be distributed across multiplecomputational systems with interruptible parallel processing, or can berun on specialized hardware for more efficient processing. Therefore,there can be an economic advantage to sending computational operationsto different types of datacenters that have different costs fordifferent types of computational operations. According to embodimentsdisclosed here, a system of one or more high-compute-cost criticaldatacenters and one or more low-compute-cost flexible datacentersprovides such an economic advantage.

A critical datacenter may have a similar configuration to a typicaldatacenter. Due to the need to reliably provide computing resources tosupport critical operations, a critical datacenter is preferablyconnected to a reliable power source, such as the power grid withmultiple redundant power supply systems. The power grid will offer aconstant power supply that the critical datacenter uses to meet theneeds of assigned computational operations. However, the grid power thatenables the critical datacenter to provide the required computationalresources is a very significant expense.

In addition, it might also be difficult to estimate future costsassociated with utilizing the critical datacenter for criticalcomputational operations. The cost for power from the power grid canfluctuate in price depending on various factors, including the locationof the critical datacenter using the power, the overall demand for thepower, weather conditions, fuel costs endured by suppliers of the powerto the power grid, and time of use, among others.

Example embodiments presented herein aim to reduce the cost associatedwith using a critical database to perform computational operations. Inparticular, some examples involve using one or more flexible datacentersto offload computational operations from a critical datacenter. Aflexible datacenter may also initially assume and support computationaloperations rather than a critical datacenter supporting thecomputational operations. As described below with regards to FIG. 2, aflexible datacenter may use behind-the-meter power in order to provideprocessing abilities and other computing resources. By usingbehind-the-meter power from renewable energy sources (e.g., wind farm600, solar farm 700) and other behind-the-meter power sources, aflexible datacenter can provide computing resources at very low costs,significantly below the costs incurred to power a critical datacenter.As such, one or more flexible datacenters may assist a criticaldatacenter in efficiently handling computational operations assigned tothe critical datacenter by one or more enterprises. The addition of oneor more flexible datacenters can also increase the quantity ofcomputational resources available to perform and support computationaloperations.

In addition, some example implementations presented herein involve theuse of queue system. A queue system is a data model that can organizecomputational operations for subsequent access and distribution toavailable datacenters, including critical datacenters and flexibledatacenters. In various embodiments, one or more control systems maysupport and maintain the queue system. For example, the remote mastercontrol system 420, the local station control system 410, or thedatacenter control system 220 may support operations of queue system. Byusing the queue system, computational operations can be organized anddistributed efficiently to datacenters that have the capabilities andavailabilities to handle the computational operations.

The structure and operation of the queue system may vary withinexamples. Particularly, the queue system may include one or more queuesthat arrange the computational operations according to a variety offactors. Example factors include parameters of each computationaloperation, deadlines for completing each computational operation, timeof submission of each computational operation, computing resourcesrequired for each computational operation, and price obtained to performeach computational operation, among others. As such, the queue systemmay organize and maintain the computational operations waiting forperformance by the critical datacenter or the flexible datacenter.

Some examples may involve using a centralized queue system maintainedcentrally by a control system. For instance, the remote master controlsystem 420 may support and maintain the queue system as a centralizedqueue. The remote master control system 420 may receive newcomputational operations requests from enterprises or other sources. Theremote master control system 420 may then place each new computationaloperation request in the centralized queue system for access anddistribution to one or more datacenters. In some examples, the remotemaster control system 420 may manage the distribution of computationaloperations to available datacenters. The distribution may involvefactoring the availability of the datacenters, the type of datacenters(e.g., critical datacenter or flexible datacenter), and the cost for adatacenter to perform the computational operation, among others. Inother examples, the data control systems at each datacenter may accessand obtain computational operations from the centralized queue system.

Some example embodiments may involve using a decentralized queue system.Particularly, the queue system may be distributed across multiplecontrol systems. For example, a first queue subsystem of thedecentralized queue system may receive and organize computationaloperations for a first set of datacenters to support and a second queuesubsystem of the decentralized queue system may receive and organizecomputational operations for a second set of datacenters to support. Thedecentralized queue system may require less computational resources tosupport and maintain. Further, by dividing computational operations intomultiple queue subsystems, sets of datacenters may be similarly dividedto quickly and efficiently address computational operations within eachsubsystem.

In various embodiments, the access to computational operations maydiffer. In some examples, the data control system or computing systemmanaging the queue system may control access to computational operationsassigned to the queue system. Particularly, the remote master controlsystem 420 or another control system may communicate and distributecomputational operations to critical datacenters and flexibledatacenters. In other examples, the control system at each datacentermay access and assume responsibility for computational operations placedwithin the queue system. This way, the datacenter control system 220 maymanage computational operations performed at the flexible datacenter 200based on capabilities and availability of the computing systems 100 atthe flexible datacenter 200.

In some examples, a critical datacenter may offload some or all of a setof computational operations to the queue system. The critical datacentermay also release some or all of the set of computational operationsdirectly to flexible datacenter. Particularly, when conditions signalthat use of a flexible datacenter is economically viable (i.e., at thesame or decreased costs relative to using power from the power grid atthe critical datacenter), a flexible datacenter may assume some or evenall of one or more sets of computational operations from the criticaldatacenter.

In some instances, a flexible datacenter may assume less criticalcomputational operations from the queue system or directly from acritical datacenter. This way, the critical datacenter may offload lesscritical computational operations directly or indirectly to a flexibledatacenter to support and manage. In such a configuration, the criticaldatacenter may continue to support critical operations assigned to thecritical datacenter by one or more enterprises while offloading lesscritical operations directly or indirectly to one or more flexibledatacenters. As a result, the critical datacenter may ensure that thecritical operations remain supported by computational resources poweredby grid power.

In other examples, a flexible datacenter may assume critical operations,augmenting the resources provided by the critical datacenter.Particularly, situations can arise where the flexible datacenter canoperate at a lower cost than the critical datacenter. For instance, oneor more behind-the-meter power sources (e.g., wind farm 600, solar farm700) may enable the flexible datacenter to operate at a lower cost thanthe critical datacenter. As a result, using the flexible datacenterinstead of the critical datacenter can lower the costs required tosupport assigned computing operations. If the situation changes suchthat the flexible datacenter is no longer less costly than the criticaldatacenter, the critical datacenter can reassume the computingoperations from the flexible datacenter.

As shown herein, by having one or more flexible datacenters powered byone or more behind-the-meter power sources available, computingoperations can be managed in a dynamic manner between the criticaldatacenter and the flexible datacenters. The dynamic management canlower costs and, in some cases, decrease the time needed to completetime-sensitive computing operations submitted to the critical datacenterby an enterprise.

In some embodiments, one or more flexible datacenters may performcomputing processes obtained through an auction process. The one or moreflexible datacenters may use behind-the-meter power to acquire andperform computational operations made available via the auction process.For example, an auction process may be used to connect companies orentities requesting computational operations to be supported andperformed at one or more datacenters with datacenters capable ofhandling the computational operations. Particularly, the auction processmay involve datacenters placing bids in a competition for the variouscomputational operations available in the auction process. For instance,the datacenter that bids to perform a computational operation at thelowest cost may win and receive the right to enter into a contract toperform the computational for the priced bid or subsequently agreedupon. As such, flexible datacenters may compete and receive the right toperform computational operations by bidding prices based on using lowcost power, such as behind-the-meter power. A datacenter control systemof a flexible datacenter may monitor available computational operationsin multiple auctions simultaneously to determine when to bid forcomputational operations based on the cost of power available andcompeting bids.

FIG. 1 shows a computing system 100 in accordance with one or moreembodiments of the present invention. Computing system 100 may includeone or more central processing units (singular “CPU” or plural “CPUs”)105, host bridge 110, input/output (“IO”) bridge 115, graphicsprocessing units (singular “GPU” or plural “GPUs”) 125, and/orapplication-specific integrated circuits (singular “ASIC or plural“ASICs”) (not shown) disposed on one or more printed circuit boards (notshown) that are configured to perform computational operations. Each ofthe one or more CPUs 105, GPUs 125, or ASICs (not shown) may be asingle-core (not independently illustrated) device or a multi-core (notindependently illustrated) device. Multi-core devices typically includea plurality of cores (not shown) disposed on the same physical die (notshown) or a plurality of cores (not shown) disposed on multiple die (notshown) that are collectively disposed within the same mechanical package(not shown).

CPU 105 may be a general purpose computational device typicallyconfigured to execute software instructions. CPU 105 may include aninterface 108 to host bridge 110, an interface 118 to system memory 120,and an interface 123 to one or more IO devices, such as, for example,one or more GPUs 125. GPU 125 may serve as a specialized computationaldevice typically configured to perform graphics functions related toframe buffer manipulation. However, one of ordinary skill in the artwill recognize that GPU 125 may be used to perform non-graphics relatedfunctions that are computationally intensive. In certain embodiments,GPU 125 may interface 123 directly with CPU 125 (and interface 118 withsystem memory 120 through CPU 105). In other embodiments, GPU 125 mayinterface 121 with host bridge 110 (and interface 116 or 118 with systemmemory 120 through host bridge 110 or CPU 105 depending on theapplication or design). In still other embodiments, GPU 125 mayinterface 133 with IO bridge 115 (and interface 116 or 118 with systemmemory 120 through host bridge 110 or CPU 105 depending on theapplication or design). The functionality of GPU 125 may be integrated,in whole or in part, with CPU 105.

Host bridge 110 may be an interface device configured to interfacebetween the one or more computational devices and IO bridge 115 and, insome embodiments, system memory 120. Host bridge 110 may include aninterface 108 to CPU 105, an interface 113 to IO bridge 115, forembodiments where CPU 105 does not include an interface 118 to systemmemory 120, an interface 116 to system memory 120, and for embodimentswhere CPU 105 does not include an integrated GPU 125 or an interface 123to GPU 125, an interface 121 to GPU 125. The functionality of hostbridge 110 may be integrated, in whole or in part, with CPU 105. IObridge 115 may be an interface device configured to interface betweenthe one or more computational devices and various IO devices (e.g., 140,145) and IO expansion, or add-on, devices (not independentlyillustrated). IO bridge 115 may include an interface 113 to host bridge110, one or more interfaces 133 to one or more IO expansion devices 135,an interface 138 to keyboard 140, an interface 143 to mouse 145, aninterface 148 to one or more local storage devices 150, and an interface153 to one or more network interface devices 155. The functionality ofIO bridge 115 may be integrated, in whole or in part, with CPU 105 orhost bridge 110. Each local storage device 150, if any, may be asolid-state memory device, a solid-state memory device array, a harddisk drive, a hard disk drive array, or any other non-transitorycomputer readable medium. Network interface device 155 may provide oneor more network interfaces including any network protocol suitable tofacilitate networked communications.

Computing system 100 may include one or more network-attached storagedevices 160 in addition to, or instead of, one or more local storagedevices 150. Each network-attached storage device 160, if any, may be asolid-state memory device, a solid-state memory device array, a harddisk drive, a hard disk drive array, or any other non-transitorycomputer readable medium. Network-attached storage device 160 may or maynot be collocated with computing system 100 and may be accessible tocomputing system 100 via one or more network interfaces provided by oneor more network interface devices 155.

One of ordinary skill in the art will recognize that computing system100 may be a conventional computing system or an application-specificcomputing system. In certain embodiments, an application-specificcomputing system may include one or more ASICs (not shown) that areconfigured to perform one or more functions, such as distributedcomputing processes or hashing, in a more efficient manner The one ormore ASICs (not shown) may interface directly with CPU 105, host bridge110, or GPU 125 or interface through IO bridge 115. Alternatively, inother embodiments, an application-specific computing system may bereduced to only those components necessary to perform a desired functionin an effort to reduce one or more of chip count, printed circuit boardfootprint, thermal design power, and power consumption. The one or moreASICs (not shown) may be used instead of one or more of CPU 105, hostbridge 110, IO bridge 115, or GPU 125. In such systems, the one or moreASICs may incorporate sufficient functionality to perform certainnetwork and computational functions in a minimal footprint withsubstantially fewer component devices.

As such, one of ordinary skill in the art will recognize that CPU 105,host bridge 110, IO bridge 115, GPU 125, or ASIC (not shown) or asubset, superset, or combination of functions or features thereof, maybe integrated, distributed, or excluded, in whole or in part, based onan application, design, or form factor in accordance with one or moreembodiments of the present invention. Thus, the description of computingsystem 100 is merely exemplary and not intended to limit the type, kind,or configuration of component devices that constitute a computing system100 suitable for performing computing operations in accordance with oneor more embodiments of the present invention.

One of ordinary skill in the art will recognize that computing system100 may be a stand-alone, laptop, desktop, server, blade, or rackmountable system and may vary based on an application or design.

FIG. 2 shows a flexible datacenter 200 in accordance with one or moreembodiments of the present invention. Flexible datacenter 200 mayinclude a mobile container 205, a behind-the-meter power input system210, a power distribution system 215, a climate control system (e.g.,250, 260, 270, 280, and/or 290), a datacenter control system 220, and aplurality of computing systems 100 disposed in one or more racks 240.Datacenter control system 220 may be a computing system (e.g., 100 ofFIG. 1) configured to dynamically modulate power delivery to one or morecomputing systems 100 disposed within flexible datacenter 200 based onbehind-the-meter power availability or an operational directive from alocal station control system (not shown), a remote master control system(not shown), or a grid operator (not shown).

In certain embodiments, mobile container 205 may be a storage trailerdisposed on wheels and configured for rapid deployment. In otherembodiments, mobile container 205 may be a storage container (not shown)configured for placement on the ground and potentially stacked in avertical or horizontal manner (not shown). In still other embodiments,mobile container 205 may be an inflatable container, a floatingcontainer, or any other type or kind of container suitable for housing amobile datacenter 200. And in still other embodiments, flexibledatacenter 200 might not include a mobile container. For example,flexible datacenter 200 may be situated within a building or anothertype of stationary environment.

Flexible datacenter 200 may be rapidly deployed on site near a source ofunutilized behind-the-meter power generation. Behind-the-meter powerinput system 210 may be configured to input power to flexible datacenter200. Behind-the-meter power input system 210 may include a first input(not independently illustrated) configured to receive three-phasebehind-the-meter alternating current (“AC”) voltage. In certainembodiments, behind-the-meter power input system 210 may include asupervisory AC-to-AC step-down transformer (not shown) configured tostep down three-phase behind-the-meter AC voltage to single-phasesupervisory nominal AC voltage or a second input (not independentlyillustrated) configured to receive single-phase supervisory nominal ACvoltage from the local station (not shown) or a metered source (notshown). Behind-the-meter power input system 210 may provide single-phasesupervisory nominal AC voltage to datacenter control system 220, whichmay remain powered at almost all times to control the operation offlexible datacenter 200. The first input (not independently illustrated)or a third input (not independently illustrated) of behind-the-meterpower input system 210 may direct three-phase behind-the-meter ACvoltage to an operational AC-to-AC step-down transformer (not shown)configured to controllably step down three-phase behind-the-meter ACvoltage to three-phase nominal AC voltage. Datacenter control system 220may controllably enable or disable generation or provision ofthree-phase nominal AC voltage by the operational AC-to-AC step-downtransformer (not shown).

Behind-the-meter power input system 210 may provide three phases ofthree-phase nominal AC voltage to power distribution system 215. Powerdistribution system 215 may controllably provide a single phase ofthree-phase nominal AC voltage to each computing system 100 or group 240of computing systems 100 disposed within flexible datacenter 200.Datacenter control system 220 may controllably select which phase ofthree-phase nominal AC voltage that power distribution system 215provides to each computing system 100 or group 240 of computing systems100. In this way, datacenter control system 220 may modulate powerdelivery by either ramping-up flexible datacenter 200 to fullyoperational status, ramping-down flexible datacenter 200 to offlinestatus (where only datacenter control system 220 remains powered),reducing power consumption by withdrawing power delivery from, orreducing power to, one or more computing systems 100 or groups 240 ofcomputing systems 100, or modulating a power factor correction factorfor the local station by controllably adjusting which phases ofthree-phase nominal AC voltage are used by one or more computing systems100 or groups 240 of computing systems 100. In some embodiments,flexible datacenter 200 may receive DC power to power computing systems100.

Flexible datacenter 200 may include a climate control system (e.g., 250,260, 270, 280, 290) configured to maintain the plurality of computingsystems 100 within their operational temperature range. In certainembodiments, the climate control system may include an air intake 250,an evaporative cooling system 270, a fan 280, and an air outtake 260. Inother embodiments, the climate control system may include an air intake250, an air conditioner or refrigerant cooling system 290, and an airouttake 260. In still other embodiments, the climate control system mayinclude a computer room air conditioner system (not shown), a computerroom air handler system (not shown), or an immersive cooling system (notshown). One of ordinary skill in the art will recognize that anysuitable heat extraction system (not shown) configured to maintain theoperation of the plurality of computing systems 100 within theiroperational temperature range may be used in accordance with one or moreembodiments of the present invention.

Flexible datacenter 200 may include a battery system (not shown)configured to convert three-phase nominal AC voltage to nominal DCvoltage and store power in a plurality of storage cells. The batterysystem (not shown) may include a DC-to-AC inverter configured to convertnominal DC voltage to three-phase nominal AC voltage for flexibledatacenter 200 use. Alternatively, the battery system (not shown) mayinclude a DC-to-AC inverter configured to convert nominal DC voltage tosingle-phase nominal AC voltage to power datacenter control system 220.

One of ordinary skill in the art will recognize that a voltage level ofthree-phase behind-the-meter AC voltage may vary based on an applicationor design and the type or kind of local power generation. As such, atype, kind, or configuration of the operational AC-to-AC step downtransformer (not shown) may vary based on the application or design. Inaddition, the frequency and voltage level of three-phase nominal ACvoltage, single-phase nominal AC voltage, and nominal DC voltage mayvary based on the application or design in accordance with one or moreembodiments of the present invention.

FIG. 3 shows a three-phase power distribution of a flexible datacenter200 in accordance with one or more embodiments of the present invention.Flexible datacenter 200 may include a plurality of racks 240, each ofwhich may include one or more computing systems 100 disposed therein. Asdiscussed above, the behind-the-meter power input system (210 of FIG. 2)may provide three phases of three-phase nominal AC voltage to the powerdistribution system (215 of FIG. 2). The power distribution system (215of FIG. 2) may controllably provide a single phase of three-phasenominal AC voltage to each computing system 100 or group 240 ofcomputing systems 100 disposed within flexible datacenter 200. Forexample, a flexible datacenter 200 may include eighteen racks 240, eachof which may include eighteen computing systems 100. The powerdistribution system (215 of FIG. 2) may control which phase ofthree-phase nominal AC voltage is provided to one or more computingsystems 100, a rack 240 of computing systems 100, or a group (e.g., 310,320, or 330) of racks 240 of computing systems 100.

In the figure, for purposes of illustration only, eighteen racks 240 aredivided into a first group of six racks 310, a second group of six racks320, and a third group of six racks 330, where each rack containseighteen computing systems 100. The power distribution system (215 ofFIG. 2) may, for example, provide a first phase of three-phase nominalAC voltage to the first group of six racks 310, a second phase ofthree-phase nominal AC voltage to the second group of six racks 320, anda third phase of three-phase nominal AC voltage to the third group ofsix racks 330. If the flexible datacenter (200 of FIG. 2) receives anoperational directive from the local station (not shown) to providepower factor correction, the datacenter control system (220 of FIG. 2)may direct the power distribution system (215 of FIG. 2) to adjust whichphase or phases of three-phase nominal AC voltage are used to providethe power factor correction required by the local station (not shown) orgrid operator (not shown). One of ordinary skill in the art willrecognize that, in addition to the power distribution, the load may bevaried by adjusting the number of computing systems 100 operativelypowered. As such, the flexible datacenter (200 of FIG. 2) may beconfigured to act as a capacitive or inductive load to provide theappropriate reactance necessary to achieve the power factor correctionrequired by the local station (not shown).

FIG. 4 shows a control distribution scheme 400 of a flexible datacenter200 in accordance with one or more embodiments of the present invention.Datacenter control system 220 may independently, or cooperatively withone or more of local station control system 410, remote master controlsystem 420, and grid operator 440, modulate power delivery to flexibledatacenter 200. Specifically, power delivery may be dynamically adjustedbased on conditions or operational directives.

Local station control system 410 may be a computing system (e.g., 100 ofFIG. 1) that is configured to control various aspects of the localstation (not independently illustrated) that generates power andsometimes generates unutilized behind-the-meter power. Local stationcontrol system 410 may communicate with remote master control system 420over a networked connection 430 and with datacenter control system 220over a networked or hardwired connection 415. Remote master controlsystem 420 may be a computing system (e.g., 100 of FIG. 1) that islocated offsite, but connected via a network connection 425 todatacenter control system 220, that is configured to provide supervisoryor override control of flexible datacenter 200 or a fleet (not shown) offlexible datacenters 200. Grid operator 440 may be a computing system(e.g., 100 of FIG. 1) that is configured to control various aspects ofthe grid (not independently illustrated) that receives power from thelocal station (not independently illustrated). Grid operator 440 maycommunicate with local station control system 440 over a networked orhardwired connection 445.

Datacenter control system 220 may monitor unutilized behind-the-meterpower availability at the local station (not independently illustrated)and determine when a datacenter ramp-up condition is met. Unutilizedbehind-the-meter power availability may include one or more of excesslocal power generation, excess local power generation that the gridcannot accept, local power generation that is subject to economiccurtailment, local power generation that is subject to reliabilitycurtailment, local power generation that is subject to power factorcorrection, conditions where the cost for power is economically viable(e.g., low cost for power), situations where local power generation isprohibitively low, start up situations, transient situations, or testingsituations where there is an economic advantage to using locallygenerated behind-the-meter power generation, specifically poweravailable at little to no cost and with no associated transmission ordistribution losses or costs.

The datacenter ramp-up condition may be met if there is sufficientbehind-the-meter power availability and there is no operationaldirective from local station control system 410, remote master controlsystem 420, or grid operator 440 to go offline or reduce power. As such,datacenter control system 220 may enable 435 behind-the-meter powerinput system 210 to provide three-phase nominal AC voltage to the powerdistribution system (215 of FIG. 2) to power the plurality of computingsystems (100 of FIG. 2) or a subset thereof. Datacenter control system220 may optionally direct one or more computing systems (100 of FIG. 2)to perform predetermined computational operations (e.g., distributedcomputing processes). For example, if the one or more computing systems(100 of FIG. 2) are configured to perform blockchain hashing operations,datacenter control system 220 may direct them to perform blockchainhashing operations for a specific blockchain application, such as, forexample, Bitcoin, Litecoin, or Ethereum. Alternatively, one or morecomputing systems (100 of FIG. 2) may be configured to independentlyreceive a computational directive from a network connection (not shown)to a peer-to-peer blockchain network (not shown) such as, for example, anetwork for a specific blockchain application, to perform predeterminedcomputational operations.

Remote master control system 420 may specify to datacenter controlsystem 220 what sufficient behind-the-meter power availabilityconstitutes, or datacenter control system 220 may be programmed with apredetermined preference or criteria on which to make the determinationindependently. For example, in certain circumstances, sufficientbehind-the-meter power availability may be less than that required tofully power the entire flexible datacenter 200. In such circumstances,datacenter control system 220 may provide power to only a subset ofcomputing systems (100 of FIG. 2), or operate the plurality of computingsystems (100 of FIG. 2) in a lower power mode, that is within thesufficient, but less than full, range of power that is available.

While flexible datacenter 200 is online and operational, a datacenterramp-down condition may be met when there is insufficient, oranticipated to be insufficient, behind-the-meter power availability orthere is an operational directive from local station control system 410,remote master control system 420, or grid operator 440. Datacentercontrol system 220 may monitor and determine when there is insufficient,or anticipated to be insufficient, behind-the-meter power availability.As noted above, sufficiency may be specified by remote master controlsystem 420 or datacenter control system 220 may be programmed with apredetermined preference or criteria on which to make the determinationindependently. An operational directive may be based on currentdispatchability, forward looking forecasts for when unutilizedbehind-the-meter power is, or is expected to be, available, economicconsiderations, reliability considerations, operational considerations,or the discretion of the local station 410, remote master control 420,or grid operator 440. For example, local station control system 410,remote master control system 420, or grid operator 440 may issue anoperational directive to flexible datacenter 200 to go offline and powerdown. When the datacenter ramp-down condition is met, datacenter controlsystem 220 may disable power delivery to the plurality of computingsystems (100 of FIG. 2). Datacenter control system 220 may disable 435behind-the-meter power input system 210 from providing three-phasenominal AC voltage to the power distribution system (215 of FIG. 2) topower down the plurality of computing systems (100 of FIG. 2), whiledatacenter control system 220 remains powered and is capable ofrebooting flexible datacenter 200 when unutilized behind-the-meter powerbecomes available again.

While flexible datacenter 200 is online and operational, changedconditions or an operational directive may cause datacenter controlsystem 220 to modulate power consumption by flexible datacenter 200.Datacenter control system 220 may determine, or local station controlsystem 410, remote master control system 420, or grid operator 440 maycommunicate, that a change in local conditions may result in less powergeneration, availability, or economic feasibility, than would benecessary to fully power flexible datacenter 200. In such situations,datacenter control system 220 may take steps to reduce or stop powerconsumption by flexible datacenter 200 (other than that required tomaintain operation of datacenter control system 220). Alternatively,local station control system 410, remote master control system 420, orgrid operator 440, may issue an operational directive to reduce powerconsumption for any reason, the cause of which may be unknown. Inresponse, datacenter control system 220 may dynamically reduce orwithdraw power delivery to one or more computing systems (100 of FIG. 2)to meet the dictate. Datacenter control system 220 may controllablyprovide three-phase nominal AC voltage to a smaller subset of computingsystems (100 of FIG. 2) to reduce power consumption. Datacenter controlsystem 220 may dynamically reduce the power consumption of one or morecomputing systems (100 of FIG. 2) by reducing their operating frequencyor forcing them into a lower power mode through a network directive.

One of ordinary skill in the art will recognize that datacenter controlsystem 220 may be configured to have a number of differentconfigurations, such as a number or type or kind of computing systems(100 of FIG. 2) that may be powered, and in what operating mode, thatcorrespond to a number of different ranges of sufficient and availableunutilized behind-the-meter power availability. As such, datacentercontrol system 220 may modulate power delivery over a variety of rangesof sufficient and available unutilized behind-the-meter poweravailability.

FIG. 5 shows a control distribution of a fleet 500 of flexibledatacenters 200 in accordance with one or more embodiments of thepresent invention. The control distribution of a flexible datacenter 200shown and described with respect to FIG. 4 may be extended to a fleet500 of flexible datacenters 200. For example, a first local station (notindependently illustrated), such as, for example, a wind farm (notshown), may include a first plurality 510 of flexible datacenters 200 athrough 200 d, which may be collocated or distributed across the localstation (not shown). A second local station (not independentlyillustrated), such as, for example, another wind farm or a solar farm(not shown), may include a second plurality 520 of flexible datacenters200 e through 200 h, which may be collocated or distributed across thelocal station (not shown). One of ordinary skill in the art willrecognize that the number of flexible datacenters 200 deployed at agiven station and the number of stations within the fleet may vary basedon an application or design in accordance with one or more embodimentsof the present invention.

Remote master control system 420 may provide supervisory control overfleet 500 of flexible datacenters 200 in a similar manner to that shownand described with respect to FIG. 4, with the added flexibility to makehigh level decisions with respect to fleet 500 that may becounterintuitive to a given station. Remote master control system 420may make decisions regarding the issuance of operational directives to agiven local station based on, for example, the status of each localstation where flexible datacenters 200 are deployed, the workloaddistributed across fleet 500, and the expected computational demandrequired for the expected workload. In addition, remote master controlsystem 420 may shift workloads from a first plurality 510 of flexibledatacenters 200 to a second plurality 520 of flexible datacenters 200for any reason, including, for example, a loss of unutilizedbehind-the-meter power availability at one local station and theavailability of unutilized behind-the-meter power at another localstation.

FIG. 6 shows a flexible datacenter 200 powered by one or more windturbines 610 in accordance with one or more embodiments of the presentinvention. A wind farm 600 typically includes a plurality of windturbines 610, each of which intermittently generates a wind-generated ACvoltage. The wind-generated AC voltage may vary based on a type, kind,or configuration of farm 600, turbine 610, and incident wind speed. Thewind-generated AC voltage is typically input into a turbine AC-to-ACstep-up transformer (not shown) that is disposed within the nacelle (notindependently illustrated) or at the base of the mast (not independentlyillustrated) of turbine 610. The turbine AC-to-AC step up transformer(not shown) outputs three-phase wind-generated AC voltage 620.Three-phase wind-generated AC voltage 620 produced by the plurality ofwind turbines 610 is collected 625 and provided 630 to another AC-to-ACstep-up transformer 640 that steps up three-phase wind-generated ACvoltage 620 to three-phase grid AC voltage 650 suitable for delivery togrid 660. Three-phase grid AC voltage 650 may be stepped down with anAC-to-AC step-down transformer 670 configured to produce three-phaselocal station AC voltage 680 provided to local station 690. One ofordinary skill in the art will recognize that the actual voltage levelsmay vary based on the type, kind, or number of wind turbines 610, theconfiguration or design of wind farm 600, and grid 660 that it feedsinto.

The output side of AC-to-AC step-up transformer 640 that connects togrid 660 may be metered and is typically subject to transmission anddistribution costs. In contrast, power consumed on the input side ofAC-to-AC step-up transformer 640 may be considered behind-the-meter andis typically not subject to transmission and distribution costs. Assuch, one or more flexible datacenters 200 may be powered by three-phasewind-generated AC voltage 620. Specifically, in wind farm 600applications, the three-phase behind-the-meter AC voltage used to powerflexible datacenter 200 may be three-phase wind-generated AC voltage620. As such, flexible datacenter 200 may reside behind-the-meter, avoidtransmission and distribution costs, and may be dynamically powered whenunutilized behind-the-meter power is available.

Unutilized behind-the-meter power availability may occur when there isexcess local power generation. In high wind conditions, wind farm 600may generate more power than, for example, AC-to-AC step-up transformer640 is rated for. In such situations, wind farm 600 may have to takesteps to protect its equipment from damage, which may include taking oneor more turbines 610 offline or shunting their voltage to dummy loads orground. Advantageously, one or more flexible datacenters 200 may be usedto consume power on the input side of AC-to-AC step-up transformer 640,thereby allowing wind farm 600 to operate equipment within operatingranges while flexible datacenter 200 receives behind-the-meter powerwithout transmission or distribution costs. The local station controlsystem (not independently illustrated) of local station 690 may issue anoperational directive to the one or more flexible datacenters 200 or tothe remote master control system (420 of FIG. 4) to ramp-up to thedesired power consumption level. When the operational directive requiresthe cooperative action of multiple flexible datacenters 200, the remotemater control system (420 of FIG. 4) may determine how to power eachindividual flexible datacenter 200 in accordance with the operationaldirective or provide an override to each flexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen grid 660 cannot, for whatever reason, take the power being producedby wind farm 600. In such situations, wind farm 600 may have to take oneor more turbines 610 offline or shunt their voltage to dummy loads orground. Advantageously, one or more flexible datacenters 200 may be usedto consume power on the input side of AC-to-AC step-up transformer 640,thereby allowing wind farm 600 to either produce power to grid 660 at alower level or shut down transformer 640 entirely while flexibledatacenter 200 receives behind-the-meter power without transmission ordistribution costs. The local station control system (not independentlyillustrated) of local station 690 or the grid operator (notindependently illustrated) of grid 660 may issue an operationaldirective to the one or more flexible datacenters 200 or to the remotemaster control system (420 of FIG. 4) to ramp-up to the desired powerconsumption level. When the operational directive requires thecooperative action of multiple flexible datacenters 200, the remotemaster control system (420 of FIG. 4) may determine how to power eachindividual flexible datacenter 200 in accordance with the operationaldirective or provide an override to each flexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen wind farm 600 is selling power to grid 660 at a negative price thatis offset by a production tax credit. In certain circumstances, thevalue of the production tax credit may exceed the price wind farm 600would have to pay to grid 660 to offload their generated power.Advantageously, one or more flexible datacenters 200 may be used toconsume power behind-the-meter, thereby allowing wind farm 600 toproduce and obtain the production tax credit, but sell less power togrid 660 at the negative price. The local station control system (notindependently illustrated) of local station 690 may issue an operationaldirective to the one or more flexible datacenters 200 or to the remotemaster control system (420 of FIG. 4) to ramp-up to the desired powerconsumption level. When the operational directive requires thecooperative action of multiple flexible datacenter 200, the remotemaster control system (420 of FIG. 4) may determine how to power eachindividual flexible datacenter 200 in accordance with the operationaldirective or provide an override to each flexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen wind farm 600 is selling power to grid 660 at a negative pricebecause grid 660 is oversupplied or is instructed to stand down and stopproducing altogether. The grid operator (not independently illustrated)may select certain power generation stations to go offline and stopproducing power to grid 660. Advantageously, one or more flexibledatacenters 200 may be used to consume power behind-the-meter, therebyallowing wind farm 600 to stop producing power to grid 660, but makingproductive use of the power generated behind-the-meter withouttransmission or distribution costs. The local station control system(not independently illustrated) of the local station 690 or the gridoperator (not independently illustrated) of grid 660 may issue anoperational directive to the one or more flexible datacenters 200 or tothe remote master control system (420 of FIG. 4) to ramp-up to thedesired power consumption level. When the operational directive requiresthe cooperative action of multiple flexible datacenters 200, the remotemaster control system (420 of FIG. 4) may determine how to power eachindividual flexible datacenter 200 in accordance with the operationaldirective or provide an override to each flexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen wind farm 600 is producing power to grid 660 that is unstable, outof phase, or at the wrong frequency, or grid 660 is already unstable,out of phase, or at the wrong frequency for whatever reason. The gridoperator (not independently illustrated) may select certain powergeneration stations to go offline and stop producing power to grid 660.Advantageously, one or more flexible datacenters 200 may be used toconsume power behind-the-meter, thereby allowing wind farm 600 to stopproducing power to grid 660, but make productive use of the powergenerated behind-the-meter without transmission or distribution costs.The local station control system (not independently illustrated) oflocal station 690 may issue an operational directive to the one or moreflexible datacenters 200 or to the remote master control system (420 ofFIG. 4) to ramp-up to the desired power consumption level. When theoperational directive requires the cooperative action of multipleflexible datacenters 200, the remote master control system (420 of FIG.4) may determine how to power each individual flexible datacenter 200 inaccordance with the operational directive or provide an override to eachflexible datacenter 200.

Further examples of unutilized behind-the-meter power availability iswhen wind farm 600 experiences low wind conditions that make it noteconomically feasible to power up certain components, such as, forexample, the local station (not independently illustrated), but theremay be sufficient behind-the-meter power availability to power one ormore flexible datacenters 200. Similarly, unutilized behind-the-meterpower availability may occur when wind farm 600 is starting up, ortesting, one or more turbines 610. Turbines 610 are frequently offlinefor installation, maintenance, and service and must be tested prior tocoming online as part of the array. One or more flexible datacenters 200may be powered by one or more turbines 610 that are offline from farm600. The above-noted examples of when unutilized behind-the-meter poweris available are merely exemplary and are not intended to limit thescope of what one of ordinary skill in the art would recognize asunutilized behind-the-meter power availability. Unutilizedbehind-the-meter power availability may occur anytime there is poweravailable and accessible behind-the-meter that is not subject totransmission and distribution costs and there is an economic advantageto using it.

One of ordinary skill in the art will recognize that wind farm 600 andwind turbine 610 may vary based on an application or design inaccordance with one or more embodiments of the present invention.

FIG. 7 shows a flexible datacenter 200 powered by one or more solarpanels 710 in accordance with one or more embodiments of the presentinvention. A solar farm 700 typically includes a plurality of solarpanels 710, each of which intermittently generates a solar-generated DCvoltage 720. Solar-generated DC voltage 720 may vary based on a type,kind, or configuration of farm 700, panel 710, and incident sunlight.Solar-generated DC voltage 720 produced by the plurality of solar panels710 is collected 725 and provided 730 to a DC-to-AC inverter 740 thatconverts solar-generated DC voltage into three-phase solar-generated ACvoltage 750. Three-phase solar-generated AC voltage 750 is provided toan AC-to-AC step-up transformer 760 that steps up three-phasesolar-generated AC voltage to three-phase grid AC voltage 790.Three-phase grid AC voltage 790 may be stepped down with an AC-to-ACstep-down transformer 785 configured to produce three-phase localstation AC voltage 777 provided to local station 775. One of ordinaryskill in the art will recognize that the actual voltage levels may varybased on the type, kind, or number of solar panels 710, theconfiguration or design of solar farm 700, and grid 790 that it feedsinto. In some embodiments, the solar farm 700 may provide DC powerdirectly to flexible datacenter 200 without a conversion to AC via theDC-to-AC inverter 740.

The output side of AC-to-AC step-up transformer 760 that connects togrid 790 may be metered and is typically subject to transmission anddistribution costs. In contrast, power consumed on the input side ofAC-to-AC step-up transformer 760 may be considered behind-the-meter andis typically not subject to transmission and distribution costs. Assuch, one or more flexible datacenters 200 may be powered by three-phasesolar-generated AC voltage 750. Specifically, in solar farm 700applications, the three-phase behind-the-meter AC voltage used to powerflexible datacenter 200 may be three-phase solar-generated AC voltage750. As such, flexible datacenter 200 may reside behind-the-meter, avoidtransmission and distribution costs, and may be dynamically powered whenunutilized behind-the-meter power is available.

Unutilized behind-the-meter power availability may occur when there isexcess local power generation. In high incident sunlight situations,solar farm 700 may generate more power than, for example, AC-to-ACstep-up transformer 760 is rated for. In such situations, solar farm 700may have to take steps to protect its equipment from damage, which mayinclude taking one or more panels 710 offline or shunting their voltageto dummy loads or ground. Advantageously, one or more flexibledatacenters 200 may be used to consume power on the input side ofAC-to-AC step-up transformer 760, thereby allowing solar farm 700 tooperate equipment within operating ranges while flexible datacenter 200receives behind-the-meter power without transmission or distributioncosts. The local station control system (not independently illustrated)of local station 775 may issue an operational directive to the one ormore flexible datacenters 200 or to the remote master control system(420 of FIG. 4) to ramp-up to the desired power consumption level. Whenthe operational directive requires the cooperative action of multipleflexible datacenters 200, the remote mater control system (420 of FIG.4) may determine how to power each individual flexible datacenter 200 inaccordance with the operational directive or provide an override to eachflexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen grid 790 cannot, for whatever reason, take the power being producedby solar farm 700. In such situations, solar farm 700 may have to takeone or more panels 710 offline or shunt their voltage to dummy loads orground. Advantageously, one or more flexible datacenters 200 may be usedto consume power on the input side of AC-to-AC step-up transformer 760,thereby allowing solar farm 700 to either produce power to grid 790 at alower level or shut down transformer 760 entirely while flexibledatacenter 200 receives behind-the-meter power without transmission ordistribution costs. The local station control system (not independentlyillustrated) of local station 775 or the grid operator (notindependently illustrated) of grid 790 may issue an operationaldirective to the one or more flexible datacenters 200 or to the remotemaster control system (420 of FIG. 4) to ramp-up to the desired powerconsumption level. When the operational directive requires thecooperative action of multiple flexible datacenters 200, the remotemaster control system (420 of FIG. 4) may determine how to power eachindividual flexible datacenter 200 in accordance with the operationaldirective or provide an override to each flexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen solar farm 700 is selling power to grid 790 at a negative pricethat is offset by a production tax credit. In certain circumstances, thevalue of the production tax credit may exceed the price solar farm 700would have to pay to grid 790 to offload their generated power.Advantageously, one or more flexible datacenters 200 may be used toconsume power behind-the-meter, thereby allowing solar farm 700 toproduce and obtain the production tax credit, but sell less power togrid 790 at the negative price. The local station control system (notindependently illustrated) of local station 775 may issue an operationaldirective to the one or more flexible datacenters 200 or to the remotemaster control system (420 of FIG. 4) to ramp-up to the desired powerconsumption level. When the operational directive requires thecooperative action of multiple flexible datacenter 200, the remotemaster control system (420 of FIG. 4) may determine how to power eachindividual flexible datacenter 200 in accordance with the operationaldirective or provide an override to each flexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen solar farm 700 is selling power to grid 790 at a negative pricebecause grid 790 is oversupplied or is instructed to stand down and stopproducing altogether. The grid operator (not independently illustrated)may select certain power generation stations to go offline and stopproducing power to grid 790. Advantageously, one or more flexibledatacenters 200 may be used to consume power behind-the-meter, therebyallowing solar farm 700 to stop producing power to grid 790, but makingproductive use of the power generated behind-the-meter withouttransmission or distribution costs. The local station control system(not independently illustrated) of the local station 775 or the gridoperator (not independently illustrated) of grid 790 may issue anoperational directive to the one or more flexible datacenters 200 or tothe remote master control system (420 of FIG. 4) to ramp-up to thedesired power consumption level. When the operational directive requiresthe cooperative action of multiple flexible datacenters 200, the remotemaster control system (420 of FIG. 4) may determine how to power eachindividual flexible datacenter 200 in accordance with the operationaldirective or provide an override to each flexible datacenter 200.

Another example of unutilized behind-the-meter power availability iswhen solar farm 700 is producing power to grid 790 that is unstable, outof phase, or at the wrong frequency, or grid 790 is already unstable,out of phase, or at the wrong frequency for whatever reason. The gridoperator (not independently illustrated) may select certain powergeneration stations to go offline and stop producing power to grid 790.Advantageously, one or more flexible datacenters 200 may be used toconsume power behind-the-meter, thereby allowing solar farm 700 to stopproducing power to grid 790, but make productive use of the powergenerated behind-the-meter without transmission or distribution costs.The local station control system (not independently illustrated) oflocal station 775 may issue an operational directive to the one or moreflexible datacenters 200 or to the remote master control system (420 ofFIG. 4) to ramp-up to the desired power consumption level. When theoperational directive requires the cooperative action of multipleflexible datacenters 200, the remote master control system (420 of FIG.4) may determine how to power each individual flexible datacenter 200 inaccordance with the operational directive or provide an override to eachflexible datacenter 200.

Further examples of unutilized behind-the-meter power availability iswhen solar farm 700 experiences intermittent cloud cover such that it isnot economically feasible to power up certain components, such as, forexample local station 775, but there may be sufficient behind-the-meterpower availability to power one or more flexible datacenters 200.Similarly, unutilized behind-the-meter power availability may occur whensolar farm 700 is starting up, or testing, one or more panels 710.Panels 710 are frequently offline for installation, maintenance, andservice and must be tested prior to coming online as part of the array.One or more flexible datacenters 200 may be powered by one or morepanels 710 that are offline from farm 700. The above-noted examples ofwhen unutilized behind-the-meter power is available are merely exemplaryand are not intended to limit the scope of what one of ordinary skill inthe art would recognize as unutilized behind-the-meter poweravailability. Behind-the-meter power availability may occur anytimethere is power available and accessible behind-the-meter that is notsubject to transmission and distribution costs and there is an economicadvantage to using it.

One of ordinary skill in the art will recognize that solar farm 700 andsolar panel 710 may vary based on an application or design in accordancewith one or more embodiments of the present invention.

FIG. 8 shows a flexible datacenter 200 powered by flare gas 800 inaccordance with one or more embodiments of the present invention. Flaregas 800 is combustible gas produced as a product or by-product ofpetroleum refineries, chemical plants, natural gas processing plants,oil and gas drilling rigs, and oil and gas production facilities. Flaregas 800 is typically burned off through a flare stack (not shown) orvented into the air. In one or more embodiments of the presentinvention, flare gas 800 may be diverted 812 to a gas-powered generatorthat produces three-phase gas-generated AC voltage 822. This power maybe considered behind-the-meter and is not subject to transmission anddistribution costs. As such, one or more flexible datacenters 200 may bepowered by three-phase gas-generated AC voltage. Specifically, thethree-phase behind-the-meter AC voltage used to power flexibledatacenter 200 may be three-phase gas-generated AC voltage 822.Accordingly, flexible datacenter 200 may reside behind-the-meter, avoidtransmission and distribution costs, and may be dynamically powered whenunutilized behind-the-meter power is available.

FIG. 9A shows a method of dynamic power delivery to a flexibledatacenter (200 of FIG. 2) using behind-the-meter power 900 inaccordance with one or more embodiments of the present invention. Instep 910, the datacenter control system (220 of FIG. 4), or the remotemaster control system (420 of FIG. 4), may monitor behind-the-meterpower availability. In certain embodiments, monitoring may includereceiving information or an operational directive from the local stationcontrol system (410 of FIG. 4) or the grid operator (440 of FIG. 4)corresponding to behind-the-meter power availability.

In step 920, the datacenter control system (220 of FIG. 4), or theremote master control system (420 of FIG. 4), may determine when adatacenter ramp-up condition is met. In certain embodiments, thedatacenter ramp-up condition may be met when there is sufficientbehind-the-meter power availability and there is no operationaldirective from the local station to go offline or reduce power. In step930, the datacenter control system (220 of FIG. 4) may enablebehind-the-meter power delivery to one or more computing systems (100 ofFIG. 2). In step 940, once ramped-up, the datacenter control system (220of FIG. 4) or the remote master control system (420 of FIG. 4) maydirect one or more computing systems (100 of FIG. 2) to performpredetermined computational operations. In certain embodiments, thepredetermined computational operations may include the execution of oneor more distributed computing processes, parallel processes, and/orhashing functions, among other types of processes.

While operational, the datacenter control system (220 of FIG. 4), or theremote master control system (420 of FIG. 4), may receive an operationaldirective to modulate power consumption. In certain embodiments, theoperational directive may be a directive to reduce power consumption. Insuch embodiments, the datacenter control system (220 of FIG. 4) or theremote master control system (420 of FIG. 4) may dynamically reducepower delivery to one or more computing systems (100 of FIG. 2) ordynamically reduce power consumption of one or more computing systems.In other embodiments, the operational directive may be a directive toprovide a power factor correction factor. In such embodiments, thedatacenter control system (220 of FIG. 4) or the remote master controlsystem (420 of FIG. 4) may dynamically adjust power delivery to one ormore computing systems (100 of FIG. 2) to achieve a desired power factorcorrection factor. In still other embodiments, the operational directivemay be a directive to go offline or power down. In such embodiments, thedatacenter control system (220 of FIG. 4) may disable power delivery toone or more computing systems (100 of FIG. 2).

As such, FIG. 9B shows a method of dynamic power delivery to a flexibledatacenter (200 of FIG. 2) using behind-the-meter power 950 inaccordance with one or more embodiments of the present invention. Instep 960, the datacenter control system (220 of FIG. 4), or the remotemaster control system (420 of FIG. 4), may monitor behind-the-meterpower availability. In certain embodiments, monitoring may includereceiving information or an operational directive from the local stationcontrol system (410 of FIG. 4) or the grid operator (440 of FIG. 4)corresponding to behind-the-meter power availability.

In step 970, the datacenter control system (220 of FIG. 4), or theremote master control system (420 of FIG. 4), may determine when adatacenter ramp-down condition is met. In certain embodiments, thedatacenter ramp-down condition may be met when there is insufficientbehind-the-meter power availability or anticipated to be insufficientbehind-the-meter power availability or there is an operational directivefrom the local station to go offline or reduce power. In step 980, thedatacenter control system (220 of FIG. 4) may disable behind-the-meterpower delivery to one or more computing systems (100 of FIG. 2). In step990, once ramped-down, the datacenter control system (220 of FIG. 4)remains powered and in communication with the remote master controlsystem (420 of FIG. 4) so that it may dynamically power the flexibledatacenter (200 of FIG. 2) when conditions change.

One of ordinary skill in the art will recognize that a datacentercontrol system (220 of FIG. 4) may dynamically modulate power deliveryto one or more computing systems (100 of FIG. 2) of a flexibledatacenter (200 of FIG. 2) based on behind-the-meter power availabilityor an operational directive. The flexible datacenter (200 of FIG. 2) maytransition between a fully powered down state (while the datacentercontrol system remains powered), a fully powered up state, and variousintermediate states in between. In addition, flexible datacenter (200 ofFIG. 2) may have a blackout state, where all power consumption,including that of the datacenter control system (220 of FIG. 4) ishalted. However, once the flexible datacenter (200 of FIG. 2) enters theblackout state, it will have to be manually rebooted to restore power todatacenter control system (220 of FIG. 4). Local station conditions oroperational directives may cause flexible datacenter (200 of FIG. 2) toramp-up, reduce power consumption, change power factor, or ramp-down.

FIG. 10 illustrates a system for managing queue distribution among acritical datacenter and behind-the-meter flexible datacenters inaccordance with one or more embodiments of the present invention. Thesystem 1000 includes a flexible datacenter 200, a critical datacenter1004, a communication link 1006, a queue system 1008, a communicationlink 1010, communication links 1012 a, 1012 b, and a remote mastercontrol system 420. The system 1000 represents an example configurationscheme for a system that can distribute computing operations using aqueue system 1008 between the critical datacenter 1004 and one or moreflexible datacenters (e.g., the flexible datacenter 200). In otherexamples, the system 1000 may include more or fewer components in otherpotential configurations. For instance, the system 1000 may not includethe queue system 1008 or may include routes that bypass the queue system1008.

The system 1000 may be configured to manage computational operationsrequested to be performed by enterprises or other entities.Computational operations may include various tasks that can be performedor generally supported by one or more computing systems within adatacenter. The parameters of each set of computational operationssubmitted by an enterprise may differ. For instance, the amount ofcomputational resources (e.g., number of computing systems), the degreeof difficulty, the duration and degree of support required, etc., mayvary for each set of computational operations. As such, the system 1000may use the queue system 1008 to organize incoming computationaloperations requests to enable efficient distribution to the flexibledatacenter 200 and the critical datacenter 1004. The system 1000 may usethe queue system 1008 to organize sets of computational operationsthereby increasing the speed of distribution and performance of thedifferent computational operations requested by various enterprises ascompared to a system without a queue system 1008.

In some examples, the queue system 1008 may enable the system 1000 toefficiently utilize the flexible datacenter 200 to perform some sets ofcomputational operations in a manner that can reduce costs or timerequired to complete the sets. In particular, one or more componentswithin the system 1000, such as the control systems 220, 420, or 1022,may be configured to identify situations that may arise where using theflexible datacenter 200 can reduce costs or increase productivity of thesystem 1000, as compared to using the critical datacenter 1004 forcomputational operations. For example, a component within the system1000, such as the control systems 220, 420, or 1022, may identify whenusing behind-the-meter power to power the computing systems 100 withinthe flexible datacenter 200 is at a lower cost compared to using thecomputing systems 1020 within the critical datacenter 1004, which arepowered by grid power. Additionally, a component in the system 1000,control systems 220, 420, or 1022, may be configured to determinesituations when offloading computational operations from the criticaldatacenter 1004 indirectly (i.e., via the queue system 1008) or directly(i.e., bypassing the queue system 1008) to the flexible datacenter 200can increase the performance allotted to the computational operationsrequested by an enterprise (e.g., reduce the time required to completetime-sensitive computational operations).

Within system 1000, the flexible datacenter 200 may represent one ormore flexible datacenters capable of offering computational processingand other computing resources using behind-the-meter power frombehind-the-meter sources, such as illustrated in FIGS. 6, 7, and 8. Asshown in FIG. 10, the flexible datacenter 200 may include abehind-the-meter power input system 215 that is connected to abehind-the-meter power source, a power distribution system 215,computing systems 100, and a datacenter control system 220, and may takethe form of a mobile container or another configuration. The flexibledatacenter 200 may additionally be connected to other power sources,such as other behind-the-meter power sources, the power grid, and/or anenergy storage system. Additionally, the flexible datacenter 200 mayinclude other components not shown in FIG. 10, such as a climate controlsystem.

The location of the flexible datacenter 200 relative to the criticaldatacenter 1004 can vary within embodiments. In some examples, theflexible datacenter 200 may be collocated with critical datacenter 1004.For instance, one or more flexible datacenters 200 may be positioned inthe same general location as the critical datacenter 1004 or even sharea building with the critical datacenter 1004. In other examples, theflexible datacenter 200 and the critical datacenter 1004 are notcollocated. Particularly, one or more flexible datacenters 200 withinthe system 1000 can have a different location from the criticaldatacenter 1004. In further examples, one or more flexible datacenters200 can share a location with the critical datacenter 1004 while otherflexible datacenters 200 can have a location away from the criticaldatacenter 1004.

In order to provide computing resources to perform or supportcomputational operations, the flexible datacenter 200 may be deployednear or otherwise connected to one or more sources of behind-the-meterpower generation. For instance, one or more flexible datacenters 200 maybe connected behind-the-meter to the wind farm 600, the solar farm 700,and/or other potentially intermittent power generation sources. As such,the behind-the-meter power input system 210 may be configured to receivebehind-the-meter power from one or more sources and input the power tothe flexible datacenter 200. For example, the behind-the-meter powerinput system 210 may provide three-phase nominal AC voltage to the powerdistribution system 215. The power distribution system 215 maycontrollably provide a single phase of three-phase nominal AC voltage toone or more computing systems 100 of flexible datacenter 200. Forinstance, power distribution system 215 may distribute power to thecomputing systems 100 individually or according to groups of computingsystems. The computing systems 100 may then use the power received fromthe behind-the-meter sources to provide processing/computing abilities,networking, storage, and other resources. In some examples, thecomputing systems 100 may include one or more ASIC computing systems,GPU computing systems, and/or CPU computing systems.

In some examples, power received at the flexible datacenter 200 mayactively switch between different behind-the-meter sources. For example,the flexible datacenter 200 may actively switch from receiving powerfrom either or both the wind farm 600 and the solar farm 700 (or othertypes of sources). A control system associated with the flexibledatacenter 200 (e.g., the datacenter control system 220) or associatedwith the system 1000 (e.g., remote master control system 420) generallymay monitor various input signals, such as, but not limited to, theprice for power, availability of power, computing analysis, and orderfrom an operator, etc., to determine which sources to receive power fromat a given time. In some situations, the control system may determinethat no source is currently a viable option for supplying power to theflexible datacenter 200. Other sources of behind-the-meter power or gridpower can also be used to power the flexible datacenter 200 withinexamples. For example, the flexible datacenter 200 may receive gridpower from the local station where it is cited.

In some examples, the datacenter control system 220 may monitor activityof the computing systems 100 within the flexible datacenter 200 and usethe activity to determine when to obtain computational operations fromthe queue system 1008. The datacenter control system 220 may analyzevarious factors prior to requesting or accessing a set of computationaloperations or an indication of the computational operations for thecomputing systems 100 to perform. The various factors may include poweravailability at the flexible datacenter 200, availability of thecomputing systems 100, type of computational operations available,estimated cost to perform the computational operations at the flexibledatacenter 200, cost for power, cost for power relative to cost for gridpower, and instructions from other components within the system 1000,among others. The datacenter control system 220 may analyze one or moreof the factors when determining whether to obtain a new set ofcomputational operations for the computing systems 100 to perform. Insuch a configuration, the datacenter control system 220 manages theactivity of the flexible datacenter 200, including determining when toacquire new sets of computational operations when capacity among thecomputing systems 100 permit.

In other examples, a component (e.g., the remote master control system420) within the system 1000 may assign or distribute one or more sets ofcomputational operations organized by the queue system 1008 to theflexible datacenter 200. For example, the remote master control system420 may manage the queue system 1008, including the distribution ofcomputational operations organized by the queue system 1008 to theflexible datacenter 1002 and the critical datacenter 1004.

The system 1000 also includes the critical datacenter 1004, whichrepresents one or more datacenters assigned to provide computationalresources to fulfill critical operations. Particularly, the criticaldatacenter 1004 may receive one or more assignments to supportcomputational operations from an enterprise. In some examples, thecritical datacenter 1004 may receive sets of computational operationsdirectly from the enterprise or the remote master control system 420.The critical datacenter 1004 may also receive sets of computationaloperations organized by the queue system 1008. As such, to warrant thatcritical operations are supported, the critical datacenter 1004 ispreferably connected to a power grid to ensure that reliable (i.e.,non-intermittent) power is available.

The critical datacenter 1004 may include a power input system 1016, apower distribution system 1018, a critical datacenter control system1022, and computing systems 1020. The power input system 1016 may beconfigured to receive power from a power grid and distribute the powerto the computing systems 1020 via the power distribution system 1018. Insome embodiments, the critical datacenter control system 1022 can managethe assignment and support of computational operations received fromenterprises, including the distribution of computational operationsamong the flexible datacenter 200 and the critical datacenter 1004. Thisis further described below with respect to remote master control system420, and management operations described with respect to remote mastercontrol system 420 may alternatively or additionally be handled bycritical datacenter control system 1022.

Similar to the flexible datacenter, the critical datacenter 1004 mayaccess and obtain sets of computational operations organized by thequeue system 1008. The critical datacenter control system 1022 maymonitor activity of the computing systems 1020 and obtain computationaloperations to perform from the queue system 1008. The criticaldatacenter control system 1022 may analyze various factors prior torequesting or accessing a set of computational operations or anindication of the computational operations for the computing systems1020 to perform. Various factors may include power availability at thecritical datacenter 1004, power availability at the flexible datacenter200, availability of the computing systems 1020, type of computationaloperations available, cost for power from the grid, estimated cost forthe critical datacenter 1004 to perform the set computationaloperations, and instructions from other components within the system1000, among others. In other examples, a component (e.g., the remotemaster control system 420) within the system 1000 may assign ordistribute one or more sets of computational operations organized by thequeue system 1008 to the critical datacenter 1004.

The communication link 1006 represents one or more links that may serveto connect the flexible datacenter 200, the critical datacenter 1004,and other components within the system 1000 (e.g., the remote mastercontrol system 420, the queue system 1008—connections not shown). Inparticular, the communication link 1006 may enable direct or indirectcommunication between the flexible datacenter 200 and the criticaldatacenter 1004. The type of communication link 1006 may depend on thelocations of the flexible datacenter 200 and the critical datacenter1004. Within embodiments, different types of communication links can beused, including but not limited to WAN connectivity, cloud-basedconnectivity, and wired and wireless communication links.

The queue system 1008 represents an abstract data type capable oforganizing computational operation requests received from enterprises.As each request for computational operations are received, the queuesystem 1008 may organize the request in some manner for subsequentdistribution to a datacenter.

Different types of queues can make up the queue system 1008 withinembodiments. The queue system 1008 may be a centralized queue thatorganizes all requests for computational operations. As a centralizedqueue, all incoming requests for computational operations may beorganized by the centralized queue.

In other examples, the queue system 1008 may be distributed consistingof multiple queue subsystems. In the distributed configuration, thequeue system 1008 may use multiple queue subsystems to organizedifferent sets of computational operations. Each queue subsystem may beused to organize computational operations based on various factors, suchas according to deadlines for completing each set of computationaloperations, locations of enterprises submitting the computationaloperations, economic value associated with the completion ofcomputational operations, and quantity of computing resources requiredto perform each set of computational operations. For instance, a firstqueue subsystem may organize sets of non-intensive computationaloperations and a second queue subsystem may organize sets of intensivecomputational operations.

Within the system 1000, the queue system 1008 is shown connected to theremote master control system 420 via the communication link 1010. Inaddition, the queue system 1008 is also shown connected to the flexibledatacenter via the communication 1012 a and to the critical datacenter1004 via the communication link 1012 b. The communication links 1010,1012 a, 1012 b may be similar to the communication link 1006 and can bevarious types of communication links within examples.

The organizational design of the queue system 1008 may vary withinexamples. In some examples, the queue system 1008 may organizeindications (e.g., tags, pointers to) to sets of computationaloperations requested by various enterprises. The queue system 1008 mayoperate as a First-In-First-Out (FIFO) data structure. In a FIFO datastructure, the first element added to the queue will be the first one tobe removed. As such, the queue system 1008 may include one or morequeues that operate using the FIFO data structure.

In some examples, one or more queues within the queue system 1008 mayuse other configurations of queues, including rules to rank or organizequeues in a particular manner that can prioritize some sets ofcomputational operations over others. The rules may include one or moreof an estimated cost and/or revenue to perform each set of computationaloperations, an importance assigned to each set of computationaloperations, and deadlines for initiating or completing each set ofcomputational operations, among others.

The queue system 1008 may include a computing system configured toorganize and maintain queues within the queue system 1008. In anotherexample, one or more other components of the system 1000 may maintainand support queues within the queue system 1008. For instance, theremote master control system 420 may maintain and support the queuesystem 1008. In other examples, multiple components may maintain andsupport the queue system 1008 in a distributed manner, such as ablockchain configuration.

In some examples, the queue system 1008 may include queue subsystemslocated at each datacenter. This way, each datacenter (e.g., via adatacenter control system) may organize computational operationsobtained at the datacenter until computing systems are able to startexecuting the computational operations.

The remote master control system 420 represents a component within thesystem 1000 that, in some embodiments, can manage the assignment andsupport of computational operations received from enterprises, includingthe distribution of computational operations among the flexibledatacenter 200 and the critical datacenter 1004. As shown in FIG. 10,the remote master control system 420 may connect to the flexibledatacenter 200 via communication link 425 and the critical datacenter1004 via communication link 1002. Alternatively or additionally, remotemaster control system 420 may connect to flexible datacenter 200 andcritical datacenter 1004 via communication link 1006 (not shown) oralternative communication links.

In some embodiments, remote master control system 420 may serve as anintermediary that facilitates all communication between flexibledatacenter 200 and critical datacenter 1004. Particularly, criticaldatacenter 1004 or flexible datacenter 200 might need to transmitcommunications to remote master control system 420 in order tocommunicate with the other datacenter. As also shown, the remote mastercontrol system 420 may connect to the queue system 1008 via thecommunication link 1010. Computational operations may be distributedbetween the queue system 1008 and the remote master control system 420via the communication link 1010.

The remote master control system 420 may assist with management ofoperations assigned to one or both of the flexible datacenter 200 andthe critical datacenter 1004. For instance, the remote master controlsystem 420 may be configured to monitor input signals frombehind-the-meter sources in order to identify situations where utilizingthe flexible datacenter 200 can reduce costs or increase efficiency ofthe system 1000. For instance, the remote master control system 420 maydetermine when flexible datacenter 200 could use power from one or morebehind-the-meter power sources to advantageously supplement thecomputing resources offered by the critical datacenter 1004.

In addition, the remote master control system 420 may manage the queuesystem 1008, including providing resources to support queues within thequeue system 1008. The remote master control system 420 may also managethe distribution of computational resources from the queue system 1008to the flexible datacenter 200 and the critical datacenter 1004. Theremote master control system 420 may communicate with the datacentercontrol system 220 in the flexible datacenter 200 via the communicationlink 425 and the critical datacenter control system 1022 in the criticaldatacenter 1004 via the communication link 1012 b. The communication mayinclude checking whether either datacenter can receive sets ofoperations. This way, the remote master control system 420 maydistribute sets of computational operations organized by the queuesystem 1008, efficiently increasing the rate which computationaloperations are completed.

As an example, the remote master control system 420 (or anothercomponent within the system 1000) may determine when power from abehind-the-meter source is being sold at a negative price back to thegrid. As another example, the remote master control system 420 maymonitor power system conditions and issue operational directives to theflexible datacenter 200. Operational directives may include, but are notlimited to, a local station directive, a remote master controldirective, a grid directive, a dispatchability directive, a forecastdirective, a workload directive based on actual behind-the-meter poweravailability or projected behind-the-meter power availability. Powersystem conditions, which may additionally or alternatively be monitoredby one or more of the control systems 220, 420, and/or 1020 may include,but are not limited to, excess local power generation at a local stationlevel, excess local power generation that a grid cannot receive, localpower generation subject to economic curtailment, local power generationsubject to reliability curtailment, local power generation subject topower factor correction, low local power generation, start up localpower generation situations, transient local power generationsituations, or testing local power generation situations where there isan economic advantage to using local behind-the-meter power generation.As another example, remote master control system 420 (or criticaldatacenter control system 1022) may monitor the types of computationaloperations requested of the critical datacenter 1004 and makedeterminations alone or in conjunction with other control systems, powersystem conditions, and/or operational directives to decide when or howto offload computational operations to a flexible datacenter 200.

As a result, the remote master control system 420 may offload some orall of the computational operations assigned to the critical datacenter1004 to the flexible datacenter 200. This way, flexible datacenter 200can reduce overall computational costs by using the behind-the-meterpower to provide computational resources to assist critical datacenter1004. The remote master control system 420 may use the queue system 1008to temporarily store and organize the offloaded computational operationsuntil a flexible datacenter (e.g., the flexible datacenter 200) isavailable to perform them. The flexible datacenter 200 consumesbehind-the-meter power without transmission or distribution costs, whichlowers the costs associated with performing computational operationsoriginally assigned to critical datacenter 1004.

In further examples, remote master control system 420 may identify othersituations that may benefit from using one or more flexible datacenters(e.g., flexible datacenter 200) to supplement or replace computationalresources provided by critical datacenter 1004.

In some examples, remote master control system 420 may facilitatecommunication among components within system 1000 using communicationlinks 425, 1002, 1006, 1010, 1012 a, and/or 1012 b. The communicationsmay include computation requests from components within system 1000. Inone embodiment, the remote master control system 420 may identify acomputational operation to be performed at a critical datacenter 1004.The computational operation may be identified by querying the criticaldatacenter 1004 or by receiving a request from the critical datacenter1004. Information regarding active or requested computational operationsat the critical datacenter 1004 may be considered as part of theidentification process. The communications may also include a variety ofother information, such as an indication of a current workload at thecritical datacenter 1004, a current status of operation at criticaldatacenter 1004 (e.g., a report indicating current capacity availableand power consumption at critical datacenter 1004). Upon receiving theinformation, the remote master control system 420 may determine whetherto route the computational operations to the flexible datacenter 200.

The determination process may involve considering various factors,including power availability and associated costs from the power gridand behind-the-meter sources, availability of flexible datacenter 200,and type and deadlines associated with assigned computationaloperations, among others. In some situations, remote master controlsystem 420 may then send the computational operation to flexibledatacenter 200 (e.g., via communication link 1006). In these situations,remote master control system 420 may determine that utilizing theflexible datacenter 200 could enhance the operation of system 1000overall (i.e. improving profitability or timely performance).Particularly, using the flexible datacenter 200 may reduce costs andincrease efficiency of system 1000. The flexible datacenter 200 may alsohelp reduce the amount of unutilized or under-utilized power beingproduced by one or more behind-the-meter sources.

In some examples, the remote master control system 420 may reassigncomputational operations from critical datacenter 1004 over to theflexible datacenter 200 for the flexible datacenter 200 to support orcomplete. For instance, the remote master control system 420 maydetermine that using the flexible datacenter 200 is more cost efficientthat only using critical datacenter 1004. As such, the remote mastercontrol system 420 may facilitate a direct transfer of responsibilityfor the computational operations from the critical datacenter 1004 tothe flexible datacenter 200. Alternatively, the remote master controlsystem 420 may use the queue system 1008 to facilitate an indirecttransfer of computational operations from the critical datacenter 1004to the flexible datacenter 200. Particularly, the remote master controlsystem 420 may transfer the offloaded computational operations from thecritical datacenter into the queue system 1008 until a flexibledatacenter 200 is able to perform the computational operations. Theflexible datacenter 200 may access and obtain the offloadedcomputational operations from the queue system 1008 or may be assignedthe computational operations from the queue system 1008 by the remotemaster control system 420 or another component within the system 1000.

In further examples, the remote master control system 420 may determinethat the flexible datacenter 200 is available to support and providecomputing resources to new computational operations received from anenterprise. This way, the remote master control system 420 may route thenew computational operations directly to the flexible datacenter 200 orindirectly via use of the queue system 1008 without impacting theworkload on the critical datacenter 1004.

When determining whether to route a computational operation to theflexible datacenter 200, the remote master control system 420 may beconfigured to consider different factors, such as the availability ofthe flexible datacenter 200 and availability of behind-the-meter power.In some situations, the remote master control system 420 or anothercomponent within the system 1000 (e.g., datacenter control system 220)may determine that the flexible datacenter 200 might not have enoughcomputing systems 100 available to satisfy the computational operation.As a result, the remote master control system 420 may refrain fromsending the computational operation to flexible datacenter 200. Theremote master control system 420 may then transmit an indication thatthe flexible datacenter 200 is unavailable back to the criticaldatacenter 1004. In some examples, the remote master control system 420may utilize the queue system 1008 to organize the computational requestsuntil a flexible datacenter or the critical datacenter 1004 isavailable.

In some examples, the remote master control system 420 may furtheranalyze the workloads of other flexible datacenters to identify aflexible datacenter that is capable of handling the computationaloperation. Upon identifying an available flexible datacenter, the remotemaster control system 420 may transmit the computational operation tothat flexible datacenter instead. In further examples, the remote mastercontrol system 420 may divide operations associated with one or moreidentified computational operation among multiple flexible datacenters.

In some examples, the remote master control system 420 may determinewhether to route a computational operation to the flexible datacenter200 based on the availability of between-the-meter power for theflexible datacenter 200. Additionally or alternatively, the remotemaster control system 420, the flexible datacenter control system 220,or another computing device may monitor one or more other power systemoperation conditions to make the determination. The remote mastercontrol system 420 may also determine whether a datacenter ramp-upcondition is met when determining whether to route a computationaloperation to the flexible datacenter 200. For instance, the remotemaster control system 420 may check whether the flexible datacenter 200is ramped-up to a fully online status, ramped-down to a fully offlinestatus, or in another state (e.g., acting as a load balancer). As such,the remote master control system 420 may determine whether to route acomputation request to the flexible datacenter 200 based on the statusof the flexible datacenter 200.

As previously discussed, the system 1000 may include a flexibledatacenter control system 220, which may be configured to modulate powerdelivery to computing systems 100 of flexible datacenter 200. Forexample, the flexible datacenter control system 220 may modulate powerdelivery to the computing systems 100 based on a threshold level ofunutilized behind-the-meter power availability or some other monitoredpower system condition. In some instances, the flexible datacentercontrol system 220 may be configured to modulate power delivery tocomputing systems 100 by selectively enabling or disabling a subset ofcomputing systems 100.

The flexible datacenter control system 220 may alternatively oradditionally be configured to modulate power delivery to the computingsystems 100 based on an operational directive. For instance, theflexible datacenter control system 220 or another system may receive anoperational directive from a user interface to modulate the powerdelivery to computing systems 100. As discussed above, the operationaldirective may be a local station directive, a remote master controldirective, a grid directive, a dispatchability directive, or a forecastdirective. In some instances, the operational directive may also includea workload directive based on a threshold level actual behind-the-meterpower availability or a threshold level of projected behind-the-meterpower availability.

FIG. 11 illustrates a system for managing queue distribution among acritical datacenter and a plurality of behind-the-meter flexibledatacenters in accordance with one or more embodiments of the presentinvention. The system 1100 is similar to the schemes illustrated in FIG.5, with the addition of the critical datacenter 1004, the queuesubsystem 1008 a, the queue subsystem 1008 b, and communication links1002, 1006 a, 1006 b, 1014 a, and 1014 b. Local stations 410 a and 410b, and other control paths not required for illustrative purposes, areremoved for clarity. Components and aspects illustrated and/or describedin FIG. 10 that are similar or the same as components or aspectsillustrated and/or described in FIG. 5 should be considered to have thesame characteristics as previously illustrated and/or described.

The system 1100 may operate similarly to the system 1000 shown in FIG.10. Similarly labeled components in FIG. 11 may have the samecharacteristics and/or capabilities as described with respect to FIG.10. The system 1100, however, is shown configured with the queue system1008 arranged in a distributed queue subsystem format (e.g., a queuesubsystem 1008 a and a queue subsystem 1008 b). Although queuesubsystems 1008 a, 1008 b are shown physically separate, the queuesubsystems 1008 a, 1008 b may be collocated and/or supported by the samecomponent of the system 1100.

The system 1100 includes the queue subsystem 1008 a connected to theremote master control system 420 via the communication link 1014 a andto flexible datacenters 200 a, 200 b, 200 c, 200 d and the criticaldatacenter 1004 via the communication link 1006 a. In such aconfiguration, the remote master control system 420, the flexibledatacenters 200 a, 200 b, 200 c, 200 d and the critical datacenter 1004may communicate with the queue subsystem 1008 a. The communication mayinvolve obtaining computational operations organized by the queuesubsystem 1008 a.

In some examples, the remote master control system 420 may distributecomputational operations organized by the queue subsystem 1008 a to theflexible datacenters 200 a, 200 b, 200 c, 200 d and the criticaldatacenter 1004. In some examples, the remote master control system 420may distribute computational operations organized by the queue subsystem1008 a to the flexible datacenters 200 e, 200 f, 200 g, 200 h, which areshown not directly connected to the queue subsystem 1008 a.

In some embodiments, the flexible datacenters 200 a, 200 b, 200 c, 200 dand the critical datacenter 1004 may communicate directly with the queuesubsystem 1008 a to obtain computational operations to perform. Thisway, control systems at each datacenter may monitor and balance theworkload supported by their computing systems.

The system 1100 also includes the queue subsystem 1008 b connected tothe remote master control system 420 via the communication link 1014 band to flexible datacenters 200 e, 200 f, 200 g, 200 h and the criticaldatacenter 1004 via the communication link 1006 b. In such aconfiguration, the remote master control system 420, the flexibledatacenters 200 e, 200 f, 200 g, 200 h and the critical datacenter 1004may communicate with the queue subsystem 1008 b. The communication mayinvolve obtaining computational operations organized by the queuesubsystem 1008 b.

In some examples, the remote master control system 420 may distributecomputational operations organized by the queue subsystem 1008 b to theflexible datacenters 200 e, 200 f, 200 g, 200 h and the criticaldatacenter 1004. In some examples, the remote master control system 420may distribute computational operations organized by the queue subsystem1008 b to the flexible datacenters 200 a, 200 b, 200 c, 200 d, which areshown not directly connected to the queue subsystem 1008 b.

In some embodiments, the flexible datacenters 200 e, 200 f, 200 g, 200 hand the critical datacenter 1004 may communicate directly with the queuesubsystem 1008 b to obtain computational operations to perform. Thisway, control systems at each datacenter may monitor and balance theworkload supported by their computing systems.

In some embodiments, the remote master control system 420 may beconfigured to determine whether to route a computational operation to aparticular flexible datacenter (e.g., flexible datacenter 200 a) fromamong multiple flexible datacenters. The determination process mayinvolve initially determining whether to route the computationaloperation to a flexible datacenter and then further selecting a specificflexible datacenter to route the computational operation to. The remotemaster control system 420 or another component (e.g., one or moreflexible datacenter control systems 220) may be configured to determinea cost of execution of the computing instructions by computing systemsat the specific flexible datacenter. Particularly, each flexibledatacenter may be capable of providing computing resources at differentcosts based on various factors, such as the locations of the flexibledatacenters 200 and the availability of behind-the-meter power to eachflexible datacenter (i.e., the flexible datacenters 200 may connect todifferent behind-the-meter power sources). As such, the remote mastercontrol system 420 may be configured to consider the different factorsto select a specific flexible datacenter to use to fulfill acomputational operation. In some examples, the remote master controlsystem 420 may use the queue subsystems 1008 a, 1008 b to temporarilyorganize sets of computational operations until a flexible datacenter orthe critical datacenter 1004 is available to perform each set.

FIG. 12 illustrates a method for managing queue distribution between acritical datacenter and a flexible datacenter in accordance with one ormore embodiments of the present invention. The method serves an exampleand may include other steps within other examples. At step 1202, themethod involves identifying, using a queue system, a computationaloperation to be performed. For instance, a component within the system1000 may identify a computational operation to be performed by analyzingthe queue system 1008. The component may be the remote master controlsystem 420, the datacenter control system 220, the critical datacentercontrol system 1022, and/or a computing system at the queue system 1008in some examples.

Identifying the computational operation can include examining varioustypes of information, such as a request for processing, networking, orstorage capabilities or a request to offload some work from the criticaldatacenter. In some instances, the computational operation may beidentified in association with an incoming computational operationrequest received from an outside enterprise. In some examples, thecomputational operation may be identified based on the organization ofthe queue system 1008. For instance, the computational operation may bethe next operation to be selected based on a FIFO format of the queuesystem 1008.

At step 1204, the method involves determining whether to route thecomputational operation to a flexible datacenter. Different componentsmay be configured to determine whether to route the computationaloperation to a flexible datacenter. For example, remote master control420 or critical datacenter control system 1022 within system 1000 may beconfigured to determine whether to route the computational operation toflexible datacenter 1002. In other examples, a flexible datacentercontrol system 220 may determine whether to route the computationaloperation to flexible datacenter 1002. For instance, the flexibledatacenter control system 220 may determine whether the computingsystems 100 have the availability to perform one or more computationaloperations within the queue system 1008. In further examples, othercomponents can perform the determination step.

Determining whether to route the computational operation to a flexibledatacenter, such as flexible datacenter 200, can involve consideringvarious factors, such as a cost of execution to provide computingresources at the flexible datacenter relative to the cost of providingcomputing resources at the critical datacenter. The determination mayalso factor the availability of the flexible datacenter as well as thecost and availability of unutilized behind-the-meter power from one ormore behind-the-meter sources. Other factors can be considered withinexamples, such as monitored power system conditions and operationaldirectives.

At step 1206, the method involves causing the computational operation tothe flexible datacenter via a communication link, such as links 1006,425, 1002, 1010, 1012 a, and/or 1012 b, based on a determination toroute the computational operation to the flexible datacenter. Sendingthe computational operation may enable computing systems of the flexibledatacenter to provide computing resources to fulfill the request.

In some examples, remote master control 420, critical datacenter controlsystem 1022, or another component within system 1000 may determine thatthe identified computational operation should be routed to the criticaldatacenter 1004. The determination may be based on various factors, suchas a cost of execution to provide computing resources at the flexibledatacenter relative to the cost of providing computing resources at thecritical datacenter. The determination may also factor theavailabilities of the critical datacenter 1004 and the flexibledatacenter 200 as well as the cost and availability of unutilizedbehind-the-meter power from one or more behind-the-meter sources. Otherfactors may be considered. As such, one or more components may route thecomputational operation to the critical datacenter 1004 to enable thecomputing systems 1020 to fulfill the computational request.

FIG. 13 illustrates a method for managing queue distribution between acritical datacenter and a plurality of flexible datacenter in accordancewith one or more embodiments of the present invention. The method servesan example and may include other steps within other examples. The methodof FIG. 13 is similar to the method of FIG. 12, and steps, components,and aspects illustrated and/or described in FIG. 13 that are similar toor the same as components or aspects illustrated and/or described inFIG. 12 should be considered to have the same characteristics aspreviously illustrated and/or described.

At step 1302, the method involves identifying, using a queue system, acomputational operation to be performed. The computational operation maybe performed at a critical datacenter, one or more flexible datacenters,or a combination of datacenters. In some examples, the queue system maybe distributed into multiple queue subsystems with each queue subsystemorganizing a set of computational operations according to rulesassociated with that queue subsystem. For example, the queue system mayinclude a first queue subsystem and a second queue subsystem where eachqueue subsystem organizes computational operations accessiblypotentially only by a subset of the plurality of flexible datacenters.For instance, a first set of flexible datacenters of the plurality offlexible may be configured to obtain computational operations from thefirst queue subsystem and a second set of flexible datacenters of theplurality of flexible datacenters are configured to obtain computationaloperations from the second queue subsystem.

At step 1304, the method involves determining whether to route thecomputational operation to a flexible datacenter in a plurality offlexible datacenters. However, in particular, multiple flexibledatacenters may be available to receive the computational operation. Assuch, a computing system, such as remote master control system 420 orcritical datacenter control system 1022, may determine whether to routethe computational operation to a flexible datacenter out of the multipleavailable.

In some examples, the determination may be made by one or moredatacenter control systems associated with the plurality of flexibledatacenters. Each datacenter control system may determine whether or notits computing systems could currently handle the computationaloperation.

At step 1306, the method involves, based on a determination to route thecomputational operation to a flexible datacenter in the plurality offlexible datacenters, determining a specific flexible datacenter in theplurality of flexible datacenters to route the computational operationto. The computing system may select a specific datacenter based on cost,availability, source of unutilized behind-the-meter power, or otherfactors. For example, the computing system may compare the costassociated with sending the computational operation to differentflexible datacenters.

In some examples, a flexible datacenter or a critical datacenter mayaccess and obtain the computational operation from the queue system. Forexample, a flexible datacenter from the plurality of flexibledatacenters may obtain the computational operation upon determining thatits computing systems are capable of supporting the computationaloperation (e.g., power is available, enough computing systems are freeto operate on the computational operation).

At step 1308, the method involves causing the computational operation tobe sent to the specific flexible datacenter via the communication link.Various components within the system may enable the computationaloperation to reach the specific flexible datacenter.

In further examples, the method described above may involve dividing thecomputational operation among multiple flexible datacenters.

Advantages of one or more embodiments of the present invention mayinclude one or more of the following:

One or more embodiments of the present invention provides a greensolution to two prominent problems: the exponential increase in powerrequired for growing blockchain operations and the unutilized andtypically wasted energy generated from renewable energy sources.

One or more embodiments of the present invention allows for the rapiddeployment of mobile datacenters to local stations. The mobiledatacenters may be deployed on site, near the source of powergeneration, and receive unutilized behind-the-meter power when it isavailable.

One or more embodiments of the present invention provide the use of aqueue system to organize computational operations and enable efficientdistribution of the computational operations to datacenters.

One or more embodiments of the present invention enable datacenters toaccess and obtain computational operations organized by a queue system.

One or more embodiments of the present invention allows for the powerdelivery to the datacenter to be modulated based on conditions or anoperational directive received from the local station or the gridoperator.

One or more embodiments of the present invention may dynamically adjustpower consumption by ramping-up, ramping-down, or adjusting the powerconsumption of one or more computing systems within the flexibledatacenter.

One or more embodiments of the present invention may be powered bybehind-the-meter power that is free from transmission and distributioncosts. As such, the flexible datacenter may perform computationaloperations, such as distributed computing processes, with little to noenergy cost.

One or more embodiments of the present invention provides a number ofbenefits to the hosting local station. The local station may use theflexible datacenter to adjust a load, provide a power factor correction,to offload power, or operate in a manner that invokes a production taxcredit and/or generates incremental revenue.

One or more embodiments of the present invention allows for continuedshunting of behind-the-meter power into a storage solution when aflexible datacenter cannot fully utilize excess generatedbehind-the-meter power.

One or more embodiments of the present invention allows for continueduse of stored behind-the-meter power when a flexible datacenter can beoperational but there is not an excess of generated behind-the-meterpower.

It will also be recognized by the skilled worker that, in addition toimproved efficiencies in controlling power delivery from intermittentgeneration sources, such as wind farms and solar panel arrays, toregulated power grids, the invention provides more economicallyefficient control and stability of such power grids in theimplementation of the technical features as set forth herein.

While the present invention has been described with respect to theabove-noted embodiments, those skilled in the art, having the benefit ofthis disclosure, will recognize that other embodiments may be devisedthat are within the scope of the invention as disclosed herein.Accordingly, the scope of the invention should be limited only by theappended claims.

What is claimed is:
 1. A system comprising: a flexible datacentercomprising: a behind-the-meter (“BTM”) power input system; a powerdistribution system; a plurality of computing systems powered by the BTMpower input system via the power distribution system; a queue systemconfigured to organize a plurality of computational operations, whereinthe queue system comprises multiple queue subsystems, and wherein eachqueue subsystem organizes a set of computational operations according torules associated with the queue subsystem; and a routing control systemconfigured to: determine, using the queue system, a computationaloperation to be performed; determine whether to route the computationaloperation to the flexible datacenter; and based on a determination toroute the computational operation to the flexible datacenter, assign thecomputational operation for performance at the flexible datacenter. 2.The system of claim 1, wherein the routing control system is a remotemaster control system positioned remotely from the flexible datacenter.3. The system of claim 1, wherein the routing control system is a remotemaster control system positioned at the flexible datacenter.
 4. Thesystem of claim 1, wherein the flexible datacenter further comprises: adatacenter control system, wherein the datacenter control system isconfigured to modulate power delivery to the plurality of computingsystems based on one or more monitored power system conditions.
 5. Thesystem of claim 4, wherein the one or more monitored power systemconditions comprises: behind-the-meter (“BTM”) power availability at theplurality of computing systems.
 6. The system of claim 4, wherein theone or more monitored power system conditions comprises: one or more ofexcess local power generation at a local station level, excess localpower generation that a grid cannot receive, local power generationsubject to economic curtailment, local power generation subject toreliability curtailment, local power generation subject to power factorcorrection, low local power generation, start up local power generationsituations, transient local power generation situations, or testinglocal power generation situations where there is an economic advantageto using local behind-the-meter power generation.
 7. The system of claim1, wherein the flexible datacenter further comprises: a datacentercontrol system, wherein the datacenter control system is configured tomodulate power delivery to the plurality of computing systems based onan operational directive.
 8. The system of claim 7, wherein theoperational directive originates from the routing control system anddepends on behind-the-meter (“BTM”) power availability at the pluralityof computing systems.
 9. The system of claim 1, wherein the BTM powerinput system is configured to receive power from a power generationsystem prior to the power undergoing step-up transformation fortransmission to a grid.
 10. The system of claim 1, wherein the routingcontrol system controls distribution of the plurality of computationaloperations from the queue system.
 11. The system of claim 1, wherein afirst queue subsystem of the queue system is located at the flexibledatacenter.
 12. The system of claim 11, further comprising: a seconddatacenter, wherein a second queue subsystem of the queue system islocated at the second datacenter.
 13. The system of claim 12, whereinthe second datacenter is a second flexible datacenter.
 14. A flexibledatacenter comprising: a behind-the-meter (“BTM”) power input system; apower distribution system; a datacenter control system; a plurality ofcomputing systems, wherein the plurality of computing systems arepowered by the BTM power input system via the power distribution system;and a queue subsystem configured to organize a set of computationaloperations for performance by the plurality of computing systems,wherein the queue subsystem is part of a distributed queue system. 15.The flexible datacenter of claim 14, wherein the distributed queuesystem includes at least two queue subsystems having different rules fororganizing computational operations.
 16. The flexible datacenter ofclaim 14, wherein the datacenter control system is configured tomodulate power delivery to the plurality of computing systems based onan operational directive received from a remote master control system.17. The flexible datacenter of claim 16, wherein the remote mastercontrol system is positioned remotely from the flexible datacenter. 18.The flexible datacenter of claim 14, wherein the BTM power input systemis configured to receive power from a power generation system prior tothe power undergoing step-up transformation for transmission to a grid.19. A method comprising: determining, by a routing control system andusing a queue system, a computation operation to be performed, whereinthe queue system organizes a plurality of computational operations andcomprises multiple queue subsystems, wherein each queue subsystemorganizes a set of computational operations according to rulesassociated with the queue subsystem; determining whether to route thecomputational operation to a flexible datacenter, wherein the flexibledatacenter comprises: (i) a behind-the-meter (“BTM”) power input system,(ii) a power distribution system, and (iii) a plurality of computingsystems powered by the BTM power input system via the power distributionsystem; and based on a determination to route the computational to theflexible datacenter, assigning the computational operation forperformance at the flexible datacenter.
 20. The method of claim 19,wherein determining whether to route the computational operation to theflexible datacenter comprises: determining to route the computationaloperation to the flexible datacenter based on BTM power availability atthe flexible datacenter.